Abstract
Metasurfaces have emerged as a powerful optical platform for imaging systems due to their compact form factor and their ability to modulate light in amplitude, phase, and polarization. In particular, metasurfaces enable multifunctional imaging by splitting incident light into multiple channels and applying distinct optical transfer functions to each channel simultaneously. When integrated with computational imaging, this capability allows the snapshot acquisition of measurements that traditionally require sequential captures, significantly improving temporal resolution while maintaining system compactness.
In this talk, Qi Guo will present a series of metasurface-enabled computational imaging systems for applications including passive depth sensing, high dynamic range (HDR) imaging, and hyperspectral imaging. Compared to conventional snapshot systems based on refractive or diffractive optics, these designs achieve substantial performance gains—for example, improving HDR dynamic range by over 10 dB. Guo will also discuss strategies to address the intrinsic chromatic aberration of metasurfaces, including a hybrid metasurface–refractive architecture that enables broadband multifunctional imaging across nearly the entire visible spectrum. Together, these results highlight a new paradigm for compact, high-performance imaging systems that combine multifunctional metasurfaces with coupled computation.
Bio
Qi Guo received a bachelor’s degree in automation from Tsinghua University, Beijing, China, in 2015, and master’s and doctoral degrees in electrical engineering from Harvard University, Cambridge, MA, USA, in 2018 and 2021, respectively. He is currently an assistant professor with the Elmore Family School of Electrical and Computer Engineering, Purdue University, where he is also affiliated with the Institute of Control, Optimization, and Networks (ICON).
His research interests include computational imaging, computer vision, and applied optics. He received the Best Paper Award at the European Conference on Computer Vision (ECCV) in 2016 and the Best Demo Award at the International Conference on Computational Photography (ICCP) in 2018. He was also the recipient of the Motorola Excellence in Teaching Award and the Ruth and Joel Spira Outstanding Teaching Award at Purdue ECE in 2025.
Guo is a member of the IEEE Technical Committee on Computational Imaging and serves as an Associate Editor for the IEEE Open Journal of Signal Processing (OJSP) and IEEE Transactions on Computational Imaging (TCI).
